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COPYRIGHT: Copyright 1999, IEE RECORD NO.: 6305291 INSPEC Abstract No: C1999-09-5260B-107 AUTHOR: Drew, M.S.; Jie Wei; Ze-Nian Li CORP SOURCE: Sch. of Comput. Sci., Simon Fraser Univ., Vancouver, BC, Canada TITLE: Illumination-invariant image retrieval and video segmentation SOURCE: Pattern Recognition, vol.32, no.8, p. 1369-88 ISSN: 0031-3203 CODEN: PTNRA8 PLACE OF PUBL: UK LANGUAGE: English PUBLISHER: Elsevier YEAR: Aug. 1999 COPYRIGHT NO: 0031-3203/99/$20.00 TREATMENT: T Theoretical or Mathematical; X Experimental RECORD TYPE: Journal Paper ABSTRACT: We show that a very simple method of discounting illumination changes is adequate for both image retrieval and video segmentation tasks. We develop a feature vector of only 36 values that can also be used for both these objectives as well as for retrieval of video proxy images from a database. The new image metric is based on a color- channel-normalization step, followed by reduction of dimensionality by going to a chromaticity space. Treating chromaticity histograms as images, we perform an effective low-pass filtering of the histogram by first reducing its resolution via a wavelet-based compression and then by a DCT transformation followed by zonal coding. We show that the color constancy step-color band normalization can be carried out in the compressed domain for images that are stored in compressed form, and that only a small amount of image information need be decompressed in order to calculate the new metric. The new method performs better than previous methods tested for image or texture recognition (30 Refs.) DESCRIPTORS: data compression; discrete cosine transforms; image coding; image retrieval; image segmentation; lighting; video signal processing; visual databases; wavelet transforms IDENTIFIERS: illumination-invariance; image retrieval; video segmentation; database; image metric; color-channel- normalization; dimensionality; chromaticity space; low-pass filtering; wavelet transform; image compression; DCT transform; zonal coding; Schust methods CLASS CODES: C5260B (Computer vision and image processing techniques); C6160S (Spatial and pictorial databases); C5260D; C1260S; C1130 (Integral transforms)Record: 13
COPYRIGHT: Copyright 1999, IEE RECORD NO.: 6234001 INSPEC Abstract No: A1999-11-0760D-005 AUTHOR: Lanz, R.; Meer, P.; Hauta-Kasari, M. CORP SOURCE: Dept. of Electr. Eng., Linkoping Univ., Sweden TITLE: Spectral-based illumination estimation and color correction SOURCE: Color Research & Application, vol.24, no.2, p. 98-111 ISSN: 0361-2317 CODEN: CREADU PLACE OF PUBL: USA LANGUAGE: English PUBLISHER: Wiley YEAR: April 1999 COPYRIGHT NO: 0361-2317/99/020098-14 TREATMENT: T Theoretical or Mathematical; X Experimental RECORD TYPE: Journal Paper ABSTRACT: We present a statistical technique to characterize the global color distribution in an image. The result can be used for color correction of a single image and for comparison of different images. It is assumed that the object colors are similar to those in a set of colors for which spectral reflectances are available (in our experiments we use spectral measurements of the Munsell and NCS color chips). The logarithm of the spectra can be approximated by finite linear combinations of a small number of basis vectors. We characterize the distributions of the expansion coefficients in an image by their modes (the most probable values). This description does not require the assumption of a special class of probability distributions and it is insensitive to outliers and other perturbations of the distributions. A change of illumination results in a global shift of the expansion coefficients and, thus, also their modes. The recovery of the illuminant is thus reduced to estimating these shift parameters. The calculated light distribution is only an estimate of the true spectral distribution of the illuminant. Direct inverse filtering for normalization may lead to undesirable results, since these processes are often ill-defined. Therefore, we apply regularization techniques in applications (such as automatic color correction) where visual appearance is important. We also demonstrate how to use this characterization of the global color distribution in an image as a tool in color- based search in image databases (34 Refs.) DESCRIPTORS: colorimetry; colour vision; optical images; probability; reflectivity; statistical analysis IDENTIFIERS: spectral-based illumination estimation; color correction; statistical technique; global color distribution; single image; object colors; spectral reflectances; spectral measurements; Munsell color chips; NCS color chips; finite linear combinations; most probable values; probability distributions; expansion coefficients; shift parameters; true spectral distribution; direct inverse filtering; regularization techniques; automatic color correction; visual appearance; color-based search; image databases; colorimetry; colour vision CLASS CODES: A0760D (Photometry and radiometry); A8732N (Colour vision: detection, adaptation and discrimination); A0250 (Probability theory, stochastic processes, and statistics); A4230 (Optical information, image formation and analysis)Record: 14
COPYRIGHT: Copyright 1999, IEE RECORD NO.: 6209258 INSPEC Abstract No: B1999-05-6135-324; C1999-05- 5260B-393 AUTHOR: Winkler, S. CORP SOURCE: Signal Process. Lab., Fed. Inst. of Technol., Lausanne, Switzerland TITLE: A perceptual distortion metric for digital color images SOURCE: Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269), p. 3 vol. (lxxi+962+984+1013), 399-403 vol.3 PLACE OF PUBL: USA ISBN: 0818688211 LANGUAGE: English PUBLISHER: IEEE Comput. Soc; Los Alamitos, CA, USA SPONSOR ORG: IEEE Signal Process. Soc CONF TITLE: Proceedings of IPCIP'98 International Conference on Image Processing CONF LOCATION: Chicago, IL, USA; 4-7 Oct. 1998 YEAR: 1998 COPYRIGHT NO: 0 8186 8821 1/98/$10.00 TREATMENT: T Theoretical or Mathematical RECORD TYPE: Conference Paper ABSTRACT: This paper presents a comprehensive distortion metric for digital color images. It is based on a normalization model of the human visual system that incorporates color perception. The model is shown to accurately fit psychophysical contrast sensitivity data as well as intra- and inter-channel contrast masking data from several different psychophysical experiments. The output of the metric is compared with subjective data for natural images (17 Refs.) DESCRIPTORS: image colour analysis IDENTIFIERS: perceptual distortion metric; digital color image; normalization model; human visual system; color perception; psychophysical contrast sensitivity data; intra-channel contrast masking data; inter-channel contrast masking data; natural images CLASS CODES: B6135; C5260B (Computer vision and image processing techniques)Record: 15
COPYRIGHT: Copyright 1999, IEE RECORD NO.: 6195097 INSPEC Abstract No: B1999-04-6135-188; C1999-04- 5260B-227 AUTHOR: Paulus, D.; Csink, L.; Niemann, H. CORP SOURCE: Lehrstuhl fur Mustererkennung, Erlangen-Nurnberg Univ., Germany TITLE: Color cluster rotation SOURCE: Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269), p. 3 vol. (lxxi+962+984+1013), 161-5 vol.1 PLACE OF PUBL: USA ISBN: 0818688211 LANGUAGE: English PUBLISHER: IEEE Comput. Soc; Los Alamitos, CA, USA SPONSOR ORG: IEEE Signal Process. Soc CONF TITLE: Proceedings of IPCIP'98 International Conference on Image Processing CONF LOCATION: Chicago, IL, USA; 4-7 Oct. 1998 YEAR: 1998 COPYRIGHT NO: 0 8186 8821 1/98/$10.00 TREATMENT: T Theoretical or Mathematical; X Experimental RECORD TYPE: Conference Paper ABSTRACT: The distribution of color values in color images depends on the illumination which varies widely under real-world conditions. We present a new approach for color normalization which adjusts the statistical properties of the distribution to predefined values. We introduce two algorithms based on geometric manipulations of the color cluster. Our new color rotation algorithm is tested on some natural and synthetic images (10 Refs.) DESCRIPTORS: computer vision; image colour analysis; image recognition; statistical analysis IDENTIFIERS: color cluster rotation; color values distribution; color images; illumination; color normalization; statistical properties; geometric manipulations; color rotation algorithm; synthetic images; natural images; computer vision; color constancy algorithms; cluster analysis CLASS CODES: B6135; B0240Z (Other topics in statistics); C5260B (Computer vision and image processing techniques); C1140Z (Other topics in statistics)Record: 21
COPYRIGHT: Copyright 1998, IEE RECORD NO.: 6015982 INSPEC Abstract No: B9810-6140C-456; C9810-5260B-249 AUTHOR: Drew, M.S.; Jie Wei; Ze-Nian Li CORP SOURCE: Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC, Canada TITLE: Illumination-invariant color object recognition via compressed chromaticity histograms of color-channel- normalized images SOURCE: Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), p. 1164, 533-40 PLACE OF PUBL: India ISBN: 8173192219 LANGUAGE: English PUBLISHER: Narosa Publishing House; New Delhi, India CONF TITLE: Proceedings of IEEE 6th International Conference on Computer Vision CONF LOCATION: Bombay, India; 4-7 Jan. 1998 YEAR: 1998 TREATMENT: T Theoretical or Mathematical RECORD TYPE: Conference Paper ABSTRACT: Several color object recognition methods that are based on image retrieval algorithms attempt to discount changes of illumination in order to increase performance when test image illumination conditions differ from those that obtained when the image database was created. Here we extend the seminal method of Swain and Ballard to discount changing illumination. The new method is based on the first stage of the simplest color indexing method, which uses angular invariants between color image and edge image channels. That method first normalizes image channels, and then effectively discards much of the remaining information. Here we adopt the color-normalization stage as an adequate color constancy step. Further, we replace 3D color histograms by 2D chromaticity histograms. Treating these as images, we implement the method in a compressed histogram-image domain using a combination of wavelet compression and Discrete Cosine Transform (DCT) to fully exploit the technique of low- pass filtering for efficiency. Results are very encouraging, with substantially better performance than other methods tested. The method is also fast, in that the indexing process is entirely carried out in the compressed domain and uses a feature vector of only 36 or 72 values (16 Refs.) DESCRIPTORS: colour; object recognition; visual databases IDENTIFIERS: color object recognition; image retrieval; image database; wavelet compression; Discrete Cosine Transform; low-pass filtering; feature vector CLASS CODES: B6140C (Optical information, image and video signal processing); C5260B (Computer vision and image processing techniques); C1250 (Pattern recognition)Record: 23
COPYRIGHT: Copyright 1998, IEE RECORD NO.: 5979505 INSPEC Abstract No: C9809-6130B-054 AUTHOR: Neumann, L.; Matkovic, K.; Purgathofer, W. EDITOR: Wolter, F.-E.; Patrikalakis, N.M. TITLE: Automatic exposure in computer graphics based on the minimum information loss principle SOURCE: Proceedings. Computer Graphics International (Cat. No.98EX149), p. xxi+800, 666-77 PLACE OF PUBL: USA ISBN: 0818684453 LANGUAGE: English PUBLISHER: IEEE Comput. Soc; Los Alamitos, CA, USA SPONSOR ORG: CGS; Comput. Graphics Div. Univ. Hannover CONF TITLE: Proceedings Computer Graphics International CONF LOCATION: Hannover, Germany; 22-26 June 1998 YEAR: 1998 COPYRIGHT NO: 0 8186 8445 3/98/$10.00 TREATMENT: P Practical RECORD TYPE: Conference Paper ABSTRACT: The available contrast of common display devices is much lower than image data often demand. Usually a variant of an average of the field of view is used to normalize the image. An alternative approach is introduced to define the mapping of rendered values to the displayable intensity range. The luminance range is chosen such that a minimum amount of information is lost thereby preserving the contrast ratio of all correctly displayed parts. The loss of information can be regulated by different error functions. If the loss is too large, the luminance range can be increased, but the original contrast is not presented any more. In this case the method represents an improvement of Schlick's (1994) mapping technique. The newly introduced method can be applied on color and gray scale images, rendered in absolute or fictitious units (34 Refs.) DESCRIPTORS: brightness; colour graphics; rendering (computer graphics) IDENTIFIERS: automatic exposure; computer graphics; minimum information loss principle; display devices; contrast; image data; field of view; image normalization; rendered value mapping; displayable intensity range; luminance range; contrast ratio; error functions; color images; gray scale images; absolute units; fictitious units CLASS CODES: C6130B (Graphics techniques)Record: 27
COPYRIGHT: Copyright 1998, IEE RECORD NO.: 5836196 INSPEC Abstract No: B9803-6140C-630; C9803-1250-315 AUTHOR: Jie Yang; Weier Lu; Waibel, A. EDITOR: Chin, R.; Pong, T.-C. CORP SOURCE: Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA TITLE: Skin-color modeling and adaptation SOURCE: Computer Vision - ACCV '98. Third Asian Conference on Computer Vision. Proceedings, p. 2 vol. (xxiv+761+757), 687-94 vol.2 PLACE OF PUBL: Germany ISBN: 3540639314 LANGUAGE: English PUBLISHER: Springer-Verlag; Berlin, Germany SPONSOR ORG: IEEE Hong Kong Sect.; Hong Kong Univ. Sci. & Technol.; Hong Kong Ind. Dept CONF TITLE: Computer Vision - ACCV'98 CONF LOCATION: Hong Kong; 8-10 Jan. 1998 YEAR: 1997 TREATMENT: P Practical; T Theoretical or Mathematical RECORD TYPE: Conference Paper ABSTRACT: This paper studies a statistical skin-color model and its adaptation. It is revealed that (1) human skin colors cluster in a small region in a color space; (2) the variance of a skin color cluster can be reduced by intensity normalization, and (3) under a certain lighting condition, a skin-color distribution can be characterized by a multivariate normal distribution in the normalized color space. We then propose an adaptive model to characterize human skin-color distributions for tracking human faces under different lighting conditions. The parameters of the model are adapted based on the maximum likelihood criterion. The model has been successfully applied to a real-time face tracker and other applications (13 Refs.) DESCRIPTORS: computer vision; face recognition IDENTIFIERS: skin-color modeling; adaptation; human skin colors; color space; intensity normalization; multivariate normal distribution; maximum likelihood criterion; real-time face tracker CLASS CODES: B6140C (Optical information, image and video signal processing); C1250 (Pattern recognition); C5260B (Computer vision and image processing techniques)Record: 28
COPYRIGHT: Copyright 1998, IEE RECORD NO.: 5836140 INSPEC Abstract No: B9803-6140C-597; C9803-5260B-394 AUTHOR: In Kyu Park; Il Dong Yun; Sang Uk Lee EDITOR: Chin, R.; Pong, T.-C. CORP SOURCE: Lab. of Real Time Vision, Seoul Nat. Univ., South Korea TITLE: A color normalization algorithm for image indexing SOURCE: Computer Vision - ACCV '98. Third Asian Conference on Computer Vision. Proceedings, p. 2 vol. (xxiv+761+757), 96-103 vol.1 PLACE OF PUBL: Germany ISBN: 3540639306 LANGUAGE: English PUBLISHER: Springer-Verlag; Berlin, Germany SPONSOR ORG: IEEE Hong Kong Sect.; Hong Kong Univ. Sci. & Technol.; Hong Kong Ind. Dept CONF TITLE: Computer Vision - ACCV'98 CONF LOCATION: Hong Kong; 8-10 Jan. 1998 YEAR: 1997 TREATMENT: T Theoretical or Mathematical RECORD TYPE: Conference Paper ABSTRACT: In this paper, a color normalization algorithm is proposed to compensate the difference of illumination between two images, which could be used for pre-processing, i.e., color constancy step in a histogram-based indexing algorithm. Unlike traditional color constancy algorithms, are attempt to transform the query image, so that the lighting condition is adjusted to be same with the reference image. The proposed algorithm assumes the Maloney and Wandel's reflectance model (1986), and normalizes the magnitude of color components of input image. Experiments are carried out to evaluate the proposed algorithm. In the experiments, it is shown that the transformed lighting condition is almost same as the reference image in the color histogram domain. In addition, it is also shown that the performance of Swain's color indexing can be enhanced by combining the proposed algorithm (12 Refs.) DESCRIPTORS: image colour analysis; indexing IDENTIFIERS: color normalization; image indexing; difference of illumination; histogram-based indexing; color constancy; color indexing CLASS CODES: B6140C (Optical information, image and video signal processing); C5260B (Computer vision and image processing techniques); C1250 (Pattern recognition)Record: 34
COPYRIGHT: Copyright 1997, IEE RECORD NO.: 5744757 INSPEC Abstract No: B9712-6140C-434; C9712-1250-183 AUTHOR: Lenz, R.; Meer, P. CORP SOURCE: Dept. of Electr. Eng., Linkoping Univ., Sweden TITLE: Color image normalization through illuminant recovery SOURCE: 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (Cat. No.97CB36052), p. 5 vol. (xxii+xxv+xxiv+xxii+4156), 3141-4 vol.4 PLACE OF PUBL: USA ISBN: 0818679190 LANGUAGE: English PUBLISHER: IEEE Comput. Soc. Press; Los Alamitos, CA, USA SPONSOR ORG: IEEE Signal Process. Soc.; DPG; GI; ITG; TUM CONF TITLE: 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing CONF LOCATION: Munich, Germany; 21-24 April 1997 YEAR: 1997 COPYRIGHT NO: 0 8186 7919 0/97/$10.00 TREATMENT: T Theoretical or Mathematical; X Experimental RECORD TYPE: Conference Paper ABSTRACT: The information in a color image is always a function of the illuminating source, the geometry, the reflectance properties of the object and the characteristic of the camera. Separating the influence of the spectral distribution of the illumination and the reflectance properties of the object is known as the color constancy problem. Successful separation is important for vision and pattern recognition tasks, quality control in the graphic arts and image database applications. We describe an approach to the color constancy problem which is based on statistical assumptions about the distribution of colors. It uses the eigenvector system of the logarithmic spectra in a large database of color samples and employs methods from robust statistics to recover the illumination spectrum. We illustrate the performance of the algorithm with a simulation in which the effect of the illumination by the standard A-source is eliminated (10 Refs.) DESCRIPTORS: eigenvalues and eigenfunctions; image colour analysis; image sampling; pattern recognition; reflectivity; spectral analysis; statistical analysis; visual databases IDENTIFIERS: color image normalization; illuminant recovery; illuminating source; geometry; reflectance properties; camera; spectral distribution; color constancy problem; pattern recognition; vision recognition; quality control; graphic arts; image database applications; statistical assumptions; color distribution; eigenvector system; logarithmic spectra; color samples; robust statistics; illumination spectrum recovery; algotithm performance; simulation CLASS CODES: B6140C (Optical information, image and video signal processing); B0240Z (Other topics in statistics); C1250 (Pattern recognition); C5260B (Computer vision and image processing techniques); C1140Z (Other topics in statistics)Record: 50
COPYRIGHT: Copyright 1995, IEE RECORD NO.: 5075104 INSPEC Abstract No: A9522-0760D-001 AUTHOR: Melgosa, M.; Hita, E.; Perez, M.M.; El Moraghi, A. CORP SOURCE: Dept. de Opt., Granada Univ., Spain TITLE: Sensitivity differences in chroma, hue, and lightness from several classical threshold datasets SOURCE: Color Research & Application, vol.20, no.4, p. 220-5 ISSN: 0361-2317 CODEN: CREADU PLACE OF PUBL: USA LANGUAGE: English YEAR: Aug. 1995 COPYRIGHT NO: 0361-2317/95/040220-06 TREATMENT: T Theoretical or Mathematical RECORD TYPE: Journal Paper ABSTRACT: A check of the weighting functions proposed by the CIE Technical Committee I-29 (TC1-29) (Color Res. Appl. 18, 137- 139 (1993)) has been carried out using pairs of samples with only a threshold difference in chroma, hue, or lightness. Experimental results with object and aperture colors were used and some parametric factors can be appointed: the dependence of Delta C* on C* appears to be about two times stronger for related color versus the aperture color mode; and the Delta H* dependence on C*, weak but significant for related colors, becomes insignificant for aperture colors. The hue-angle dependences of H* after correction for C* and the dependences of Delta L* on L* or C* are found not significant for aperture colors. After normalization of the five different datasets employed, the results achieved are in overall good agreement and support the proposal of the CIE TC1-29 (25 Refs.) DESCRIPTORS: brightness; colorimetry; sensitivity IDENTIFIERS: sensitivity differences; chroma; hue; lightness; classical threshold datasets; weighting functions; CIE Technical Committee; threshold difference; aperture colors; parametric factors; aperture color mode; hue-angle dependences; colorimetry CLASS CODES: A0760D (Photometry and radiometry)Record: 54
RECORD NO.: 4770426 INSPEC Abstract No: B9411-7220-004; C9411-5530-002 AUTHOR: Kubo, M.; Takahashi, K. CORP SOURCE: Miyanodai Technol. Dev. Center, Fuji Photo Film Co. Ltd., Japan TITLE: Color reproduction of full-color hardcopy system-image processing in Pictrography 2500 SOURCE: Journal of the Institute of Image Electronics Engineers of Japan, vol.22, no.3, p. 233-7 ISSN: 0285-9831 PLACE OF PUBL: Japan LANGUAGE: Japanese YEAR: June 1993 TREATMENT: P Practical RECORD TYPE: Journal Paper ABSTRACT: Fuji Photo Film Co. developed Pictrography 2500 aimed at high-fidelity reproduction of CRT images. The authors describe the characteristics of 'Pictrography 2500', its development purpose and history, image processing system, image processing algorithm (CRT calibration-normalization of input signals, color correspondence-image projection, and conversion into printing signal-normalization of output signals), and hardware systems. Pictrography 2500 has been highly valued for its color fidelity compared to the existing systems (2 Refs.) DESCRIPTORS: image processing equipment IDENTIFIERS: colour reproduction; full-color hardcopy system; Pictrography 2500; Fuji Photo Film Co.; CRT images; image processing system; image processing algorithm CLASS CODES: B7220 (Signal processing and conditioning equipment and techniques); C5530 (Pattern recognition and computer vision equipment)Record: 57
RECORD NO.: 4399029 INSPEC Abstract No: A9311-8732N-004 AUTHOR: Lucassen, M.P.; Walraven, J. CORP SOURCE: TNO Inst. for Perception, Soesterberg, Netherlands TITLE: Quantifying color constancy: evidence for nonlinear processing of cone-specific contrast SOURCE: Vision Research, vol.33, no.5-6, p. 739-57 ISSN: 0042-6989 CODEN: VISRAM PLACE OF PUBL: UK LANGUAGE: English YEAR: March-April 1993 COPYRIGHT NO: 0042-6989/93/$6.00+0.00 TREATMENT: B Bibliography; X Experimental RECORD TYPE: Journal Paper ABSTRACT: Color constancy was studied by the method of comparing color samples under two different illuminants using a CRT color monitor. In addition to the classical approach in which one of the illuminants is a (standard) white, the authors performed experiments in which the range of differential illumination was extended by using pairs of lights that were both colored. The stimulus pattern consisted of an array of thirty-five colour samples (including five neutral samples) on a white background. A trichromatic illuminant-object interaction was simulated analogous to that resulting from illumination by three monochromatic lights. The test samples, as seen under 'test' and 'match' illumination, were successively presented to the left and right eye (haploscopic matching). The data show systematic deviations from predictions on the basis of cone-specific normalization procedures like those incorporated in the Retinex algorithm and the von Kries transformation. The results can be described by a nonlinear response transformation that depends on two factors, receptor-specific sample/background contrast and the extent to which the illuminant stimulates the receptor system in question. The latter factor explains the deviations. These are mainly caused by the short-wave- sensitive system, as a consequence of the fact that this system can be more selectively stimulated than the other, spectrally less separated, cone systems (68 Refs.) DESCRIPTORS: colour vision; visual perception IDENTIFIERS: color constancy quantification; left eye; match illumination; color samples comparison; standard white; test illumination; nonlinear processing; cone-specific contrast; illuminants; CRT color monitor; neutral samples; trichromatic illuminant-object interaction; monochromatic lights; right eye; haploscopic matching; systematic deviations; cone-specific normalization procedures; Retinex algorithm; von Kries transformation; receptor system; short- wave-sensitive system CLASS CODES: A8732N (Colour detection; adaptation and discrimination); A8732S (Psychophysics of vision, visual perception, binocular vision)Record: 58
RECORD NO.: 4343448 INSPEC Abstract No: A9306-8732N-002 AUTHOR: McCann, J.J. CORP SOURCE: Vision Res. Lab., Polaroid, Cambridge, MA, USA TITLE: Color constancy: small overall and large local changes SOURCE: Proc. SPIE - Int. Soc. Opt. Eng. (USA), Proceedings of the SPIE - The International Society for Optical Engineering, vol.1666, p. 310-21 ISSN: 0277-786X CODEN: PSISDG PLACE OF PUBL: USA LANGUAGE: English SPONSOR ORG: SPIE; Soc. Imaging Sci. Technol CONF TITLE: Human Vision, Visual Processing and Digital Display III CONF LOCATION: San Jose, CA, USA; 10-13 Feb. 1992 YEAR: 1992 COPYRIGHT NO: 0 8194 0820 4/92/$4.00 TREATMENT: X Experimental RECORD TYPE: Conference Paper; Journal Paper ABSTRACT: The author describes a two-part study of the human visual system's mechanism for normalization in color constancy. By combining the Tatami and the center-surround experiments a number of conclusions about the human color-constancy mechanism are drawn. Exact color constancy is achieved by exactly equal quanta catches everywhere in the field of view. The introduction of global changes in quanta catch cause small appearance changes. This is very different from local changes in quanta catch that cause large appearance changes. The human color constancy mechanism normalizes sensations to the maxima in the field of view; it normalizes each waveband separately (Retinex). The mechanism controlling color constancy uses the individual maxima in each wave band to calculate color sensations (12 Refs.) DESCRIPTORS: colour vision IDENTIFIERS: Tatami experiment; center-surround experiments; human color- constancy; field of view; global changes; Retinex; individual maxima CLASS CODES: A8732N (Colour detection; adaptation and discrimination)Record: 76
RECORD NO.: 2274081 INSPEC Abstract No: B84037842 AUTHOR: Chen, W.; Pratt, W.K. CORP SOURCE: Compression Labs. Inc., San Jose, CA, USA TITLE: Scene adaptive coder SOURCE: IEEE Transactions on Communications, vol.COM-32, no.3, p. 225-32 ISSN: 0090-6778 CODEN: IECMBT PLACE OF PUBL: USA LANGUAGE: English YEAR: March 1984 COPYRIGHT NO: 0090-6778/84/0300-0225$01.00 TREATMENT: T Theoretical or Mathematical; X Experimental RECORD TYPE: Journal Paper ABSTRACT: An efficient single-pass adaptive bandwidth compression technique using the discrete cosine transform is described. The coding process involves a simple thresholding and normalization operation on the transform coefficients. Adaptivity is achieved by using a rate buffer for channel rate equalization. The buffer status and input rate are monitored to generate a feedback normalization factor. Excellent results are demonstrated for coding of color images at 0.4 bit/pixel corresponding to real-time color television transmission over a 1.5 Mbit/s channel (15 Refs.) DESCRIPTORS: codecs; encoding; picture processing; television equipment IDENTIFIERS: colour TV transmission; colour images; scene adaptive coder; transform image coding; coding/decoding system; adaptive bandwidth compression; discrete cosine transform; coding; thresholding; normalization; transform coefficients; rate buffer; channel rate equalization; feedback normalization factor CLASS CODES: B6120B (Codes); B6140C (Optical information, image and video signal processing); B6430 (Television equipment, systems and applications)
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